AI-Rad Companion Prostate MR

Siemens Healthineers

AI-Rad Companion Prostate MR aims to aid the MR/US fusion for biopsy workflow by automatically segmenting the prostate and performing volumetry of the prostate gland. The segmentation of the prostate gland is automatically detected and displayed as contour for the radiologist. The volume of the segmentation gland is automatically computed and provided for inclusion in the final report. The results can be exported as a RTSS object which is then used in TRUS-guided biopsy by the urologist.
Product specifications Information source: Vendor
Last updated: Nov. 20, 2022
Product name AI-Rad Companion Prostate MR
Company Siemens Healthineers
Subspeciality Abdomen
Modality MR
Disease targeted Prostate cancer
Key-features Prostate segmentation and volume estimation, aided annotation of lesion, calculation of PSA density, exporting results in RTSS format
Suggested use During: perception aid (prompting all abnormalities/results/heatmaps)
Data characteristics
Input 2D TSE axial or 3D TSE / SPACE MR image data, Single-frame data format
Input format DICOM
Output Image annotations, Report with table of results, RTSS
Output format DICOM, RTSS
Integration Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone webbased
Deployment Cloud-based
Trigger for analysis Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time 1 - 10 minutes
Certified, Class IIb , MDR
510(k) cleared, Class II
Market presence
On market since 05-2020
Distribution channels Teamplay Digital Health Platform
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Subscription
Based on Number of analyses
Peer reviewed papers on performance

  • Deep learning algorithm performs similarly to radiologists in the assessment of prostate volume on MRI (read)

  • A concurrent, deep learning – based computer-aided detection system for prostate multiparametric MRI: a performance study involving experienced and less-experienced radiologists (read)

  • A Novel Deep Learning Based Computer-Aided Diagnosis System Improves the Accuracy and Efficiency of Radiologists in Reading Biparametric Magnetic Resonance Images of the Prostate: Results of a Multireader, Multicase Study. (read)

Non-peer reviewed papers on performance
Other relevant papers